3 papers
eess.SP2025
A Correction for the Paper "Symplectic geometry mode decomposition and its application to rotating machinery compound fault diagnosis"
Hong-Yan Zhang, Haoting Liu, Rui-Jia Lin +1
The symplectic geometry mode decomposition (SGMD) is a powerful method for decomposing time series, which is based on the diagonal averaging principle (DAP) inherited from the sing…
eess.SP2025
Pulling Back Theorem for Generalizing the Diagonal Averaging Principle in Symplectic Geometry Mode Decomposition and Singular Spectrum Analysis
Hong-Yan Zhang, Haoting Liu, Zhi-Qiang Feng +4
The symplectic geometry mode decomposition (SGMD) is a powerful method for analyzing time sequences. The SGMD is based on the upper conversion via embedding and down conversion via…
math.ST2025
High Order Expansion Method for Kuiper's Statistic in Goodness-of-fit Test
Hong-Yan Zhang, Zhi-Qiang Feng, Haoting Liu +2
Kuiper's statistic, a measure for comparing the difference of ideal distribution and empirical distribution, is of great significance in the goodness-of-fit test. However, Ku…